Currently, UAVs are widely used in military and civilian fields to accomplish various types of tasks such as target reconnaissance, target tracking, intelligence gathering, post-quake rescue and geological exploration. For example, in the case of collaborative target reconnaissance by multiple UAVs, it is necessary to allocate the most appropriate reconnaissance target to each UAV, and also to plan an optimal flight path for each UAV. This concerns the joint optimization of task assignment and path planning constrained by a plurality of factors and is also a non-deterministic problem.
With the deepening of UAV research, environmental factors are gradually incorporated into the study. Especially with respect to the UAV task assignment, path planning and flight control, it is the main tasks of the current UAV research in terms of how to reduce the UAV energy consumption and how to control the flight state to enable the UAV to perform most tasks with least fuel consumption with better task performance and higher security under the influence of such environmental factors. Currently, the models commonly used to solve the UAV task assignment and task planning problems include TSP (Traveling Salesman Problem) model, TOP (Team Orienteering Problem) model and VRP (Vehicle Routing Problem) model. The TSP model minimizes the path cost of the traveler after passing through all the given target points when there is only a single traveler. The TOP model allows each teamer to visit as many target points as possible, thereby maximizing the total return of all teamers when there are multiple teamers. The VRP model allows the vehicle to visit a certain number of target points where each target point can only be visited once, thereby minimizing the total distance or total time consumed by the UAVs when there is a fixed number of vehicles.
In the process of implementing the embodiments of the present invention, the inventor finds that in the actual operation of the existing technical solutions, it is generally assumed that the speed of the UAV in the model is constant within a constant time. However, this assumption is obviously unrealistic. As a result, it is impossible to accurately simulate the UAV's actual state of motion using the model, and thus achieve optimal path planning.